Research On Collaborative Optimization Method Based On Joint Optimization And Its Application In Power Plant Flue Gas Removal System

As the flue gas pollutants of coal-fired power plants become more and more serious,the corresponding environmental protection policies have been put forward one after another,and the combination of coal-fired power plants and flue gas removal system arises at the right moment.The flue gas removal system of coal-fired power plant is a complex coupling system.During the removal process,part of the removal devices will cooperate with other pollutants when removing the corresponding pollutants.Therefore,it is particularly important to carry out overall optimization of the system to achieve low cost and efficient removal.Multidisciplinary design optimization method is an effective method to solve such problems.It makes full use of the coupling relationship between subsystems,designs corresponding coordination strategies,and optimizes solution in parallel,to improve the optimization efficiency of the system.Collaborative optimization method is a typical multi-level optimization method of multidisciplinary design optimization method.Because of its unique distributed double-layer structure and advanced solution strategy,it has been widely promoted and applied.Therefore,it is of great significance to combine the collaborative optimization method with the flue gas removal system of coal-fired power plants.The main research contents of this paper are as follows:(1)A collaborative optimization method based on global and local optimization was proposed to solve the problems of standard collaborative optimization method and response surface collaborative optimization method to solve the problem of low precision.In the global optimization stage,different approximate models are used for different dimensional problems to approximate the consistency constraints of the system and reduce the complexity of the solution of the system.In the process of optimization,the range of sampling points is dynamically updated according to the inconsistent information to obtain as much spatial information as possible,and finally converges to the vicinity of the global optimal solution.In the local optimization stage,the system level and discipline level were analyzed and improved,the optimization algorithm with better accuracy and stability was selected,and the optimization solution in the global stage was used as the initial point to obtain the global optimal solution accurately and quickly at last.Finally,through the simulation experiments of two numerical examples,it is proved that the improved method has great advantages compared with other optimization methods,which can reduce the convergence times and ensure the precision of the solution.(2)To solve the difficult problems caused by the high complexity and high coupling of the flue gas removal system.Through the research and analysis of the cost model of each removal device,the flue gas removal system is combined with the collaborative optimization method based on joint optimization to generate a collaborative optimization framework for the flue gas removal system of coal-fired power plants,the system is decomposed into the system level with the total operating cost of the removal system as the optimization objective,and the three sub-disciplines of desulfurization,denitrification and dust removal,their constraints are the emission standards of various pollutants and the adjustable operating conditions of each device.Finally,case simulations are carried out under a variety of working conditions and different initial points,which further proves the advantages of the improved method compared to other optimization methods,at the same time compared to the standard collaborative optimization and the whole particle swarm optimization simulation results,the improved collaborative optimization method is verified in the smoke removal system on the practicability and effectiveness.